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Estimation of fetal lung development using quantitative analysis of ultrasonographic images in normal canine pregnancy
We investigated the quantitative analysis of sonographic images to predict fetal lung maturity of the canine foetus in normal pregnancy. Twelve bitches were recruited in the present study. Serial ultrasonographic exams were performed at three pre-determined time periods corresponding to the pseudogl...
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Published in: | Theriogenology 2017-07, Vol.96, p.158-163 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We investigated the quantitative analysis of sonographic images to predict fetal lung maturity of the canine foetus in normal pregnancy. Twelve bitches were recruited in the present study. Serial ultrasonographic exams were performed at three pre-determined time periods corresponding to the pseudoglandular (40–48 days of pregnancy), canalicular (49–56 days of pregnancy) and saccular phase (57–63 days of pregnancy) of lung development. Mean grey level (MGL) and the standard deviation of the histogram (SDH) of fetal lung and liver sonographic images were measured with dedicated software. The lung-to-liver ratio (LLR) for both parameters was also calculated. Measurements were taken on the two caudal-most foetuses and then averaged. SDH did not show any statistically significant difference between the three time periods in the lungs or in the liver. MGL measured in the lungs significantly increased in the first period and reached a plateau during the last two periods. Liver echogenicity was constant during the first two periods and significantly increased during the last week of gestation. The LLR of MGL significantly decreased during the last week of pregnancy. The LLR was a very good test to detect fetal lung maturity (area under the receiver operator curve (AUROC) = 0.875); using a cut-off value of LLR |
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ISSN: | 0093-691X 1879-3231 |
DOI: | 10.1016/j.theriogenology.2017.03.011 |